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1.
Abstract

Mobile, location-aware computing technology is widely available. In this article we sketch out a manifesto on mobile computing in geographic education (MoGeo) for consideration and debate within the geographic community. At the core of our argument is the idea that emerging mobile computing technologies will allow teachers to bring the classroom and pedagogic materials into the field, and that the resulting in situ educational experience will enhance learning by contextualizing the complex and abstract concepts that we teach. We provide a set of key principles that can guide the development of field experiences for students using these new technologies.  相似文献   

2.
High performance computing has undergone a radical transformation during the past decade. Though monolithic supercomputers continue to be built with significantly increased computing power, geographically distributed computing resources are now routinely linked using high‐speed networks to address a broad range of computationally complex problems. These confederated resources are referred to collectively as a computational Grid. Many geographical problems exhibit characteristics that make them candidates for this new model of computing. As an illustration, we describe a spatial statistics problem and demonstrate how it can be addressed using Grid computing strategies. A key element of this application is the development of middleware that handles domain decomposition and coordinates computational functions. We also discuss the development of Grid portals that are designed to help researchers and decision makers access and use geographic information analysis tools.  相似文献   

3.
分布式水文模型的并行计算研究进展   总被引:3,自引:1,他引:2  
大流域、高分辨率、多过程耦合的分布式水文模拟计算量巨大,传统串行计算技术不能满足其对计算能力的需求,因此需要借助于并行计算的支持。本文首先从空间、时间和子过程三个角度对分布式水文模型的可并行性进行了分析,指出空间分解的方式是分布式水文模型并行计算的首选方式,并从空间分解的角度对水文子过程计算方法和分布式水文模型进行了分类。然后对分布式水文模型的并行计算研究现状进行了总结。其中,在空间分解方式的并行计算方面,现有研究大多以子流域作为并行计算的基本调度单元;在时间角度的并行计算方面,有学者对时空域双重离散的并行计算方法进行了初步研究。最后,从并行算法设计、流域系统综合模拟的并行计算框架和支持并行计算的高性能数据读写方法3个方面讨论了当前存在的关键问题和未来的发展方向。  相似文献   

4.
Consumer users of maps on mobile devices are producing noteworthy geographic knowledges in the contexts of their own lives that are distinct from those of professional data scientists. By leveraging the streaming nature of big data in mobile maps and zooming multiscalar views, consumer users' mobile map practices produce a popular, multiscalar form of visual geographic knowledge that is both enabled and limited by its big data assemblage and associated technologies. The first half of this article outlines the role of consumer user practices amidst spatial big data assemblages, not for volunteered geographic information or aggregate analysis but for contextual, everyday use. Consumer users and their knowledges are coconstituted through mobile map viewing and as materially limited technological practices. This article focuses specifically on the consumer users' concept of scale in this context, for Web-based maps' multiscalar views differentiate them from older maps. The second half analyzes mobile map consumer users' concepts of scale in a series of focus groups that involved both questions and observing participants' actions with maps on their own phones. Instead of passively accepting maps at predetermined optimized scales from the map application, consumer users actively viewed the map across scales while searching but not while navigating.  相似文献   

5.
基于面向服务的分布式空间信息支撑平台,从高可信网络计算环境、高可信空间信息、高可信软件、高可信计算平台4方面探讨构建GIS高可信服务计算环境的方法及其关键技术。为实现GIS空间信息存储的可靠性和发布的安全性,建立了基于角色访问控制权限的空间数据管理模型,并研究空间信息发布的中间件技术,展望构建GIS高可信服务计算环境的发展趋势和突破点。  相似文献   

6.
基于社会感知计算的游客时空行为研究   总被引:4,自引:2,他引:2  
李君轶  唐佳  冯娜 《地理科学》2015,35(7):814-821
在情景感知、大数据、移动互联网和物联网发展的大背景下,迎合社会感知计算发展的趋势,探讨旅游社会感知计算内涵及其应用。在分析了现实地理世界、游客行为研究和社会感知计算之间关系的基础上,探讨旅游管理、传感器、游客活动和推理机的相互作用,构建了四位一体的游客行为社会感知计算概念模型。同时以西安国内游客为例,在新浪微博数据的支持和旅游社会感知计算框架下,探讨西安国内游客的时空共现和旅游流空间转移,探明了游客之间的相互关系和旅游空间行为及旅游流空间网络特征,为游客行为研究提供了思路和借鉴。同时在目前社会感知计算研究进展的基础上,展望了旅游社会感知计算未来的发展方向。  相似文献   

7.
This article provides a decentralized and coordinate-free algorithm, called decentralized gradient field (DGraF), to identify critical points (peaks, pits, and passes) and the topological structure of the surface network connecting those critical points. Algorithms that can operate in the network without centralized control and without coordinates are important in emerging resource-constrained spatial computing environments, in particular geosensor networks. Our approach accounts for the discrepancies between finite granularity sensor data and the underlying continuous field, ignored by previous work. Empirical evaluation shows that our DGraF algorithm can improve the accuracy of critical points identification when compared with the current state-of-the-art decentralized algorithm and matches the accuracy of a centralized algorithm for peaks and pits. The DGraF algorithm is efficient, requiring O(n) overall communication complexity, where n is the number of nodes in the geosensor network. Further, empirical investigations of our algorithm across a range of simulations demonstrate improved load balance of DGraF when compared with an existing decentralized algorithm. Our investigation highlights a number of important issues for future research on the detection of holes and the monitoring of dynamic events in a field.  相似文献   

8.
This article presents an algorithm for decentralized (in-network) data mining of the movement pattern flock among mobile geosensor nodes. The algorithm DDIG (Deferred Decentralized Information Grazing) allows roaming sensor nodes to ‘graze’ over time more information than they could access through their spatially limited perception range alone. The algorithm requires an intrinsic temporal deferral for pattern mining, as sensor nodes must be enabled to collect, memorize, exchange, and integrate their own and their neighbors' most current movement history before reasoning about patterns. A first set of experiments with trajectories of simulated agents showed that the algorithm accuracy increases with growing deferral. A second set of experiments with trajectories of actual tracked livestock reveals some of the shortcomings of the conceptual flocking model underlying DDIG in the context of a smart farming application. Finally, the experiments underline the general conclusion that decentralization in spatial computing can result in imperfect, yet useful knowledge.  相似文献   

9.
张姗琪  甄峰  秦萧  唐佳 《地理研究》2020,39(7):1580-1591
科学准确地感知社区居民参与现状、诊断存在问题,及时广泛地了解社区居民需求与诉求,对于提升新形势下社区居民参与城市社区规划的能力与水平意义重大。借助网络和移动设备等技术手段,采取以人为主体的参与式感知方式获取数据,可实时感知和分析居民的情感、行为和所处的环境,进而提高社区居民参与的广泛性和时效性。国内外该领域的研究刚刚起步,对面向城市社区规划的参与式感知与计算尚缺乏系统深入的机理探索和方法研究。本文针对中国城市社区规划的实际需求,构建了面向城市社区规划的参与式感知与计算概念模型,提出实现参与式感知与计算的技术框架,并探讨其中涉及的具体技术研究内容。本研究将深化面向城市社区的参与式感知与计算的相关理论与方法研究,为城市社区规划的公众参与和科学评估提供新思路、新方法。  相似文献   

10.
Abstract

Appropriate diffusion of geographic information technologies is hampered by lack of systematic research on factors and processes affecting diffusion, utilization and impact assessment of the technologies and by a variety of conceptual and methodological problems. Diffusion of innovation principles developed in other fields, in combination with methods developed within the field of management information systems, provide an important beginning for improved understanding. This paper focuses on gaps in knowledge which might be addressed within the geographic information field by analysis techniques and research methodologies used in the diffusion of innovations.  相似文献   

11.
Artificial neural networks (ANNs) have been extensively used for the spatially explicit modeling of complex geographic phenomena. However, because of the complexity of the computational process, there has been an inadequate investigation on the parameter configuration of neural networks. Most studies in the literature from GIScience rely on a trial-and-error approach to select the parameter setting for ANN-driven spatial models. Hyperparameter optimization provides support for selecting the optimal architectures of ANNs. Thus, in this study, we develop an automated hyperparameter selection approach to identify optimal neural networks for spatial modeling. Further, the use of hyperparameter optimization is challenging because hyperparameter space is often large and the associated computational demand is heavy. Therefore, we utilize high-performance computing to accelerate the model selection process. Furthermore, we involve spatial statistics approaches to improve the efficiency of hyperparameter optimization. The spatial model used in our case study is a land price evaluation model in Mecklenburg County, North Carolina, USA. Our results demonstrate that the automated selection approach improves the model-level performance compared with linear regression, and the high-performance computing and spatial statistics approaches are of great help for accelerating and enhancing the selection of optimal neural networks for spatial modeling.  相似文献   

12.
With the ubiquity of advanced web technologies and location-sensing hand held devices, citizens regardless of their knowledge or expertise, are able to produce spatial information. This phenomenon is known as volunteered geographic information (VGI). During the past decade VGI has been used as a data source supporting a wide range of services, such as environmental monitoring, events reporting, human movement analysis, disaster management, etc. However, these volunteer-contributed data also come with varying quality. Reasons for this are: data is produced by heterogeneous contributors, using various technologies and tools, having different level of details and precision, serving heterogeneous purposes, and a lack of gatekeepers. Crowd-sourcing, social, and geographic approaches have been proposed and later followed to develop appropriate methods to assess the quality measures and indicators of VGI. In this article, we review various quality measures and indicators for selected types of VGI and existing quality assessment methods. As an outcome, the article presents a classification of VGI with current methods utilized to assess the quality of selected types of VGI. Through these findings, we introduce data mining as an additional approach for quality handling in VGI.  相似文献   

13.
分布式水文模型软件系统研究综述   总被引:3,自引:1,他引:2  
分布式水文模型软件系统作为分布式水文模型的技术外壳,是模型应用的重要技术保障。当前分布式水文模型应用呈现出多过程综合模拟、用户群范围广和计算量大的特点,对分布式水文模型软件系统的灵活性、易用性和高效性提出了更高的要求。本文首先分析了分布式水文模型应用的主要流程,之后从应用视角对现有分布式水文模型软件系统的特点进行了归纳,主要结论为:①软件系统按照模型结构灵活性的高低分为以下3种类型:不支持子过程选择和算法设置,不支持子过程选择、但支持算法设置,同时支持子过程选择和算法设置;②根据用户操作数据预处理软件方式的不同,参数提取方式分为菜单/命令行式和向导式;③按照模型的程序实现方法分为串行和并行方式,按照模型运行环境分为本地和网络模式。现有软件系统在灵活性、易用性和高效性方面存在如下问题:一是尚未解决模型结构灵活性和对用户知识依赖性之间的矛盾;二是现有菜单/命令行式和向导式的参数提取方式步骤繁琐,难以实现参数的自动提取;三是模型大多为串行方式和本地模式,容易遇到计算瓶颈问题。最后从模块化、智能化、网络化及移动化、并行化和虚拟仿真等方面探讨了分布式水文模型软件系统的发展趋势和研究方向。  相似文献   

14.
Performing point pattern analysis using Ripley’s K function on point events of large size is computationally intensive as it involves massive point-wise comparisons, time-consuming edge effect correction weights calculation, and a large number of simulations. This article presented two strategies to optimize the algorithm for point pattern analysis using Ripley’s K function and utilized cloud computing to further accelerate the optimized algorithm. The first optimization sorted the points on their x and y coordinates and thus narrowed the scope of searching for neighboring points down to a rectangular area around each point in estimating K function. Using the actual study area in computing edge effect correction weights is essential to estimate an unbiased K function, but is very computationally intensive if the study area is of complex shape. The second optimization reused the previously computed weights to avoid repeating expensive weights calculation. The optimized algorithm was then parallelized using Open Multi-Processing (OpenMP) and hybrid Message Passing Interface (MPI)/OpenMP on the cloud computing platform. Performance testing showed that the optimizations effectively accelerated point pattern analysis using K function by a factor of 8 using both the sequential version and the OpenMP-parallel version of the optimized algorithm. While the OpenMP-based parallelization achieved good scalability with respect to the number of CPU cores utilized and the problem size, the hybrid MPI/OpenMP-based parallelization significantly shortened the time for estimating K function and performing simulations by utilizing computing resources on multiple computing nodes. Computational challenge imposed by point pattern analysis tasks on point events of large size involving a large number of simulations can be addressed by utilizing elastic, distributed cloud resources.  相似文献   

15.
论地理学的特性与基本问题   总被引:4,自引:1,他引:3  
学科通常都具有独立的研究对象、独立的学科问题、独特的学科特征以及独特的社会服务功能。本文从3个方面论述了地理学的属性,进而认识现代地理学的时代特征。①地理学研究对象的演化经历了由简单向复杂的变化过程。在研究实践过程中,应充分认识地理系统的复杂属性。②地理的要素、空间与时间相互融合构成了独特的学科问题体系,阐述了不同地理问题的本质区别,进而促进解决不同地理问题的技术与方法体系建设。③“还原论”与“整体论”并举的地理学哲学思维方兴未艾。地理学强调的综合研究在当今时代受到了前所未有的重视。在新兴学科和新兴技术的支撑下,出现了地理要素和地理系统并行研究的新格局。本文从地理学研究的基本特征出发,总结了地理学研究的核心问题,探讨地理学驱动机制对地理规律的组合效应。理解地理学关键特征和时代价值,有助于探索地理学的社会发展契机。  相似文献   

16.
This article explores the notion of a system of ontologies specifically designed for the needs of an information science. A framework for geographic information ontologies is outlined that focuses on geographic information constructs rather than on the direct representation of real-world entities or on linguistic terms. The framework takes the form of a generative hierarchy anchored by the notion of intentionality at one end and of a spatiotemporal field of potentially relevant information at the other. Two theoretical notions are used in the generation of the hierarchy. The first is the principle of semantic contraction, whereby, starting from a level of geographic information constructs specified so as to reflect user intentionality, semantically coherent domains of properties are removed over several steps until only the rudiments of a spatiotemporal information system are left. The second notion is that of object of discourse, which allows entities to be represented as the composites of geographic information constructs at the higher levels of the hierarchy, explicitly reflecting the connections between the purpose, function, appropriate internal constitution, and ensuing categorization of the entities represented. The framework's main contribution is thus twofold: first, it allows the notions of user purpose and object function to be directly built into geographic representations; second, it proposes a hierarchy of ontological levels that are linked by systematic semantic relations. Further, the framework presents an integrated view of object and field representations. It may also provide a novel perspective on a number of issues of ongoing interest in geographic information science.  相似文献   

17.
Recent developments in miniaturization of computing devices, in location‐sensing technology and in ubiquitous short‐range wireless networks enable new types of social behaviour. This paper investigates one novel application of these technologies, ad hoc inner‐urban shared‐ride trip planning: Transportation clients such as pedestrians are seeking ad hoc shared rides from transportation hosts such as private automobiles, buses, taxi cabs or trains. While centralized trip planners are challenged by assigning clients and hosts in an ad hoc manner, in particular for non‐scheduled hosts, we consider the transportation network as a mobile geosensor network of agents that interact locally by short‐range communication and heuristic wayfinding strategies. This approach is not only fully scalable; we can also demonstrate that with short‐range communication, and hence, incomplete transportation network knowledge a system still can deliver near‐to‐optimal trips.  相似文献   

18.
基于定位视频的车辆导航原型系统设计与关键技术研究   总被引:1,自引:0,他引:1  
基于电子地图的导航系统相对抽象且缺乏沉浸感,不方便用户判别。为使导航效果更加直观和生动,该文提出基于定位视频的车辆导航思路,对车辆导航原型系统进行总体设计与实现,并探讨其关键技术。核心思想是建立道路定位视频(Geo-video)数据库,利用移动终端和固定目标的位置信息对定位视频数据库进行空间检索,将相应位置的视频图像传输给移动终端并实现路线和目标指引。试验证明该方法在技术上具有可行性。  相似文献   

19.
To improve the efficiency of planning and designing silt dam systems, this article employs theories and technologies of collaboration and distributed virtual geographic environments (VGEs) to construct a collaborative virtual geographic environment (CVGE) system. The CVGE system provides geographically distributed users with a shared virtual space and a collaborative platform to implement collaborative planning. Many difficulties have been found in integrating data resources and model procedures for the planning of silt dam systems because of their diversity in heterogeneous environments. Unlike most of the current distributed system applications, the proposed CVGE system not only supports multi-platform and multi-program-language interoperability in the dynamically changing network environment, but also shares programs, data and software in the collaborative environment. Based on creating a shared 3D space by virtual reality technology, agent and grid technologies were tightly coupled to develop the CVGE system. A grid-based multi-agent system service framework was designed to implement this new paradigm for the CVGE system, which efficiently integrates and shares geographically distributed resources as well as having the ability to build modelling procedures on different platforms. At the same time, mobile agent computing services were implemented to reduce the network load, process parallel tasks, enhance communication efficiency and adapt dynamically to the changing network environment. Using Java, JMF (Java Media Framework API), Globus Toolkits (GT) core, Voyager, C++, and the OpenGL development package, a prototype system was developed to support silt dam systems planning in the case study area, the Jiu-Yuan-Gou watershed of the Loess Plateau, China. Compared with the traditional workflow, the CVGE system can reduce the workload by between one third and a half.  相似文献   

20.
Geographically Weighted Regression (GWR) is a widely used tool for exploring spatial heterogeneity of processes over geographic space. GWR computes location-specific parameter estimates, which makes its calibration process computationally intensive. The maximum number of data points that can be handled by current open-source GWR software is approximately 15,000 observations on a standard desktop. In the era of big data, this places a severe limitation on the use of GWR. To overcome this limitation, we propose a highly scalable, open-source FastGWR implementation based on Python and the Message Passing Interface (MPI) that scales to the order of millions of observations. FastGWR optimizes memory usage along with parallelization to boost performance significantly. To illustrate the performance of FastGWR, a hedonic house price model is calibrated on approximately 1.3 million single-family residential properties from a Zillow dataset for the city of Los Angeles, which is the first effort to apply GWR to a dataset of this size. The results show that FastGWR scales linearly as the number of cores within the High-Performance Computing (HPC) environment increases. It also outperforms currently available open-sourced GWR software packages with drastic speed reductions – up to thousands of times faster – on a standard desktop.  相似文献   

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